Parameter Identification and Monitoring of Mechanical Systems Under Nonlinear Vibration

Development of new sensors and digital processors has provided opportunity for identification of nonlinear systems. Vibration measurements have become standard for predicting and monitoring machinery in industry. Parameter Identification and Monitoring of Mechanical Systems under Nonlinear Vibration focusses on methods for the identification of nonlinearities in mechanical systems, giving description and examples of practical application. Chapters cover nonlinear dynamics; nonlinear vibrations; signal processing; parameter identification; application of signal processing to mechanical systems; practical experience and industrial applications; and synchronization of nonlinear systems.

• Covers the most recent advances in machinery monitoring
• Describes the basis for nonlinear dynamics
• Presents advantages of applying modern signal processing to mechanical systems

Aerospace and Automobile Engineering graduate students, Researchers and Professors

• Dedication
• List of figures
• About the author
• Introduction
  • Abstract
  • Dynamics
• 1: Linear vibrations
  • Abstract
  • 1.1 Introduction
  • 1.2 Single degree of freedom
  • 1.3 Multiple degrees of freedom
• 2: Nonlinear vibrations
  • Abstract
  • 2.1 Introduction
  • 2.2 Jump phenomena
  • 2.3 Self-excited vibrations
• 3: Signal processing
  • Abstract
  • 3.1 Introduction
  • 3.2 Convolution theorem
  • 3.3 Fourier Transform
  • 3.4 Short Time Fourier Transform (STFT)
  • 3.5 Wavelet Transform
  • 3.6 Discrete Wavelet Transform
  • 3.7 Phase diagram
  • 3.8 Approximate entropy
• 4: Parameter identification
  • Abstract
  • 4.1 Introduction
  • 4.2 Time domain analysis
  • 4.3 Frequency domain analysis
• 5: Application of signal processing to mechanical systems
  • Abstract
  • 5.1 Introduction
  • 5.2 Roller bearings
  • 5.3 Gears
  • 5.4 Friction
• 6: Practical experience and industrial applications
  • Abstract
  • 6.1 Introduction
  • 6.2 Test procedure
  • 6.3 Simulation analysis
• 7: Synchronization of nonlinear systems
  • Abstract
  • 7.1 Introduction
  • 7.2 Synchronization
  • 7.3 Kuramoto’s model
  • 7.4 Synchronization of nonlinear pendulums
• Bibliography
• Index